Fuzzy adaptive control system of a non-stationary plant with closed-loop passive identifier / F. Manenti [et al.]

Уровень набора: Resource-Efficient TechnologiesАльтернативный автор-лицо: Manenti, F., specialist in the field of automation equipment and electronics, researcher of Tomsk Polytechnic University, 1977-, Flavio;Francesco, R., Rossi;Goryunov, A. G., Specialist in the field of automatic control, Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences, 1979-, Aleksey Germanovich;Dyadik, V. F., specialist in the field of automatic control systems, associate Professor of Tomsk Polytechnic University, candidate of technical Sciences, 1939-, Valery Feodosievich;Kozin, K. A., specialist in the field of automation and electronics, Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences, 1980-, Kirill Andreevich;Nadezhdin, I. S., specialist in the field of automation equipment and electronics, engineer-researcher of Tomsk Polytechnic University, 1990-, Igor Sergeevich;Mikhalevich, S. S., specialist in the field of automatic control, Engineer-designer of Tomsk Polytechnic University, 1988-, Sergey SergeevichКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет (ТПУ), Физико-технический институт (ФТИ), Кафедра электроники и автоматики физических установок (№ 24) (ЭАФУ)Язык: английский.Резюме или реферат: Typically chemical processes have significant nonlinear dynamics, but despite this, industry is conventionally still using PID-based regulatory control systems. Moreover, process units are interconnected, in terms of inlet and outlet material/energy flows, to other neighboring units, thus their dynamic behavior is strongly influenced by these connections and, as a consequence, conventional control systems performance often proves to be poor. This paper proposes a hybrid fuzzy PID control logic, whose tuning parameters are provided in real time. The fuzzy controller tuning is made on the basis of Mamdani controller, also exploiting the results coming from an identification procedure that is carried on when an unmeasured step disturbance of any shape affects the process behavior.In addition, this paper compares a fuzzy logic based PID with PID regulators whose tuning is performed by standard and well-known methods. In some cases the proposed tuning methodology ensures a control performance that is comparable to that guaranteed by simpler and more common tuning methods. However, in case of dynamic changes in the parameters of the controlled system, conventionally tuned PID controllers do not show to be robust enough, thus suggesting that fuzzy logic based PIDs are definitively more reliable and effective..Примечания о наличии в документе библиографии/указателя: [References: p. 17-18 (60 tit.)].Тематика: электронный ресурс | труды учёных ТПУ | PID-controller | identification | Fuzzy controller Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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[References: p. 17-18 (60 tit.)]

Typically chemical processes have significant nonlinear dynamics, but despite this, industry is conventionally still using PID-based regulatory control systems. Moreover, process units are interconnected, in terms of inlet and outlet material/energy flows, to other neighboring units, thus their dynamic behavior is strongly influenced by these connections and, as a consequence, conventional control systems performance often proves to be poor. This paper proposes a hybrid fuzzy PID control logic, whose tuning parameters are provided in real time. The fuzzy controller tuning is made on the basis of Mamdani controller, also exploiting the results coming from an identification procedure that is carried on when an unmeasured step disturbance of any shape affects the process behavior.In addition, this paper compares a fuzzy logic based PID with PID regulators whose tuning is performed by standard and well-known methods. In some cases the proposed tuning methodology ensures a control performance that is comparable to that guaranteed by simpler and more common tuning methods. However, in case of dynamic changes in the parameters of the controlled system, conventionally tuned PID controllers do not show to be robust enough, thus suggesting that fuzzy logic based PIDs are definitively more reliable and effective.

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